Source code for airflow.providers.amazon.aws.operators.ecs

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from __future__ import annotations

import re
import sys
from datetime import timedelta
from typing import TYPE_CHECKING, Sequence

import boto3

from airflow.compat.functools import cached_property
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator, XCom
from airflow.providers.amazon.aws.exceptions import EcsOperatorError, EcsTaskFailToStart
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.providers.amazon.aws.hooks.ecs import (
    EcsClusterStates,
    EcsHook,
    EcsTaskDefinitionStates,
    EcsTaskLogFetcher,
    should_retry_eni,
)
from airflow.utils.helpers import prune_dict
from airflow.utils.session import provide_session

if TYPE_CHECKING:
    from airflow.utils.context import Context

[docs]DEFAULT_CONN_ID = "aws_default"
[docs]class EcsBaseOperator(BaseOperator): """This is the base operator for all Elastic Container Service operators.""" def __init__(self, *, aws_conn_id: str | None = DEFAULT_CONN_ID, region: str | None = None, **kwargs): self.aws_conn_id = aws_conn_id self.region = region super().__init__(**kwargs) @cached_property
[docs] def hook(self) -> EcsHook: """Create and return an EcsHook.""" return EcsHook(aws_conn_id=self.aws_conn_id, region_name=self.region)
@cached_property
[docs] def client(self) -> boto3.client: """Create and return the EcsHook's client.""" return self.hook.conn
[docs] def execute(self, context: Context): """Must overwrite in child classes.""" raise NotImplementedError("Please implement execute() in subclass")
[docs]class EcsCreateClusterOperator(EcsBaseOperator): """ Creates an AWS ECS cluster. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:EcsCreateClusterOperator` :param cluster_name: The name of your cluster. If you don't specify a name for your cluster, you create a cluster that's named default. :param create_cluster_kwargs: Extra arguments for Cluster Creation. :param wait_for_completion: If True, waits for creation of the cluster to complete. (default: True) :param waiter_delay: The amount of time in seconds to wait between attempts, if not set then the default waiter value will be used. :param waiter_max_attempts: The maximum number of attempts to be made, if not set then the default waiter value will be used. """
[docs] template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
def __init__( self, *, cluster_name: str, create_cluster_kwargs: dict | None = None, wait_for_completion: bool = True, waiter_delay: int | None = None, waiter_max_attempts: int | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.cluster_name = cluster_name self.create_cluster_kwargs = create_cluster_kwargs or {} self.wait_for_completion = wait_for_completion self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context): self.log.info( "Creating cluster %r using the following values: %s", self.cluster_name, self.create_cluster_kwargs, ) result = self.client.create_cluster(clusterName=self.cluster_name, **self.create_cluster_kwargs) cluster_details = result["cluster"] cluster_state = cluster_details.get("status") if cluster_state == EcsClusterStates.ACTIVE: # In some circumstances the ECS Cluster is created immediately, # and there is no reason to wait for completion. self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state) elif self.wait_for_completion: waiter = self.hook.get_waiter("cluster_active") waiter.wait( clusters=[cluster_details["clusterArn"]], WaiterConfig=prune_dict( { "Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts, } ), ) return cluster_details
[docs]class EcsDeleteClusterOperator(EcsBaseOperator): """ Deletes an AWS ECS cluster. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:EcsDeleteClusterOperator` :param cluster_name: The short name or full Amazon Resource Name (ARN) of the cluster to delete. :param wait_for_completion: If True, waits for creation of the cluster to complete. (default: True) :param waiter_delay: The amount of time in seconds to wait between attempts, if not set then the default waiter value will be used. :param waiter_max_attempts: The maximum number of attempts to be made, if not set then the default waiter value will be used. """
[docs] template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
def __init__( self, *, cluster_name: str, wait_for_completion: bool = True, waiter_delay: int | None = None, waiter_max_attempts: int | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.cluster_name = cluster_name self.wait_for_completion = wait_for_completion self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context): self.log.info("Deleting cluster %r.", self.cluster_name) result = self.client.delete_cluster(cluster=self.cluster_name) cluster_details = result["cluster"] cluster_state = cluster_details.get("status") if cluster_state == EcsClusterStates.INACTIVE: # In some circumstances the ECS Cluster is deleted immediately, # so there is no reason to wait for completion. self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state) elif self.wait_for_completion: waiter = self.hook.get_waiter("cluster_inactive") waiter.wait( clusters=[cluster_details["clusterArn"]], WaiterConfig=prune_dict( { "Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts, } ), ) return cluster_details
[docs]class EcsDeregisterTaskDefinitionOperator(EcsBaseOperator): """ Deregister a task definition on AWS ECS. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:EcsDeregisterTaskDefinitionOperator` :param task_definition: The family and revision (family:revision) or full Amazon Resource Name (ARN) of the task definition to deregister. If you use a family name, you must specify a revision. :param wait_for_completion: If True, waits for creation of the cluster to complete. (default: True) :param waiter_delay: The amount of time in seconds to wait between attempts, if not set then the default waiter value will be used. :param waiter_max_attempts: The maximum number of attempts to be made, if not set then the default waiter value will be used. """
[docs] template_fields: Sequence[str] = ("task_definition", "wait_for_completion")
def __init__( self, *, task_definition: str, wait_for_completion: bool = True, waiter_delay: int | None = None, waiter_max_attempts: int | None = None, **kwargs, ): super().__init__(**kwargs) self.task_definition = task_definition self.wait_for_completion = wait_for_completion self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context): self.log.info("Deregistering task definition %s.", self.task_definition) result = self.client.deregister_task_definition(taskDefinition=self.task_definition) task_definition_details = result["taskDefinition"] task_definition_arn = task_definition_details["taskDefinitionArn"] task_definition_state = task_definition_details.get("status") if task_definition_state == EcsTaskDefinitionStates.INACTIVE: # In some circumstances the ECS Task Definition is deleted immediately, # so there is no reason to wait for completion. self.log.info("Task Definition %r in state: %r.", task_definition_arn, task_definition_state) elif self.wait_for_completion: waiter = self.hook.get_waiter("task_definition_inactive") waiter.wait( taskDefinition=task_definition_arn, WaiterConfig=prune_dict( { "Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts, } ), ) return task_definition_arn
[docs]class EcsRegisterTaskDefinitionOperator(EcsBaseOperator): """ Register a task definition on AWS ECS. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:EcsRegisterTaskDefinitionOperator` :param family: The family name of a task definition to create. :param container_definitions: A list of container definitions in JSON format that describe the different containers that make up your task. :param register_task_kwargs: Extra arguments for Register Task Definition. :param wait_for_completion: If True, waits for creation of the cluster to complete. (default: True) :param waiter_delay: The amount of time in seconds to wait between attempts, if not set then the default waiter value will be used. :param waiter_max_attempts: The maximum number of attempts to be made, if not set then the default waiter value will be used. """
[docs] template_fields: Sequence[str] = ( "family", "container_definitions", "register_task_kwargs", "wait_for_completion",
) def __init__( self, *, family: str, container_definitions: list[dict], register_task_kwargs: dict | None = None, wait_for_completion: bool = True, waiter_delay: int | None = None, waiter_max_attempts: int | None = None, **kwargs, ): super().__init__(**kwargs) self.family = family self.container_definitions = container_definitions self.register_task_kwargs = register_task_kwargs or {} self.wait_for_completion = wait_for_completion self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context): self.log.info( "Registering task definition %s using the following values: %s", self.family, self.register_task_kwargs, ) self.log.info("Using container definition %s", self.container_definitions) response = self.client.register_task_definition( family=self.family, containerDefinitions=self.container_definitions, **self.register_task_kwargs, ) task_definition_details = response["taskDefinition"] task_definition_arn = task_definition_details["taskDefinitionArn"] task_definition_state = task_definition_details.get("status") if task_definition_state == EcsTaskDefinitionStates.ACTIVE: # In some circumstances the ECS Task Definition is created immediately, # so there is no reason to wait for completion. self.log.info("Task Definition %r in state: %r.", task_definition_arn, task_definition_state) elif self.wait_for_completion: waiter = self.hook.get_waiter("task_definition_active") waiter.wait( taskDefinition=task_definition_arn, WaiterConfig=prune_dict( { "Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts, } ), ) context["ti"].xcom_push(key="task_definition_arn", value=task_definition_arn) return task_definition_arn
[docs]class EcsRunTaskOperator(EcsBaseOperator): """ Execute a task on AWS ECS (Elastic Container Service) .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:EcsRunTaskOperator` :param task_definition: the task definition name on Elastic Container Service :param cluster: the cluster name on Elastic Container Service :param overrides: the same parameter that boto3 will receive (templated): https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ecs.html#ECS.Client.run_task :param aws_conn_id: connection id of AWS credentials / region name. If None, credential boto3 strategy will be used (https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html). :param region: region name to use in AWS Hook. Override the region in connection (if provided) :param launch_type: the launch type on which to run your task ('EC2', 'EXTERNAL', or 'FARGATE') :param capacity_provider_strategy: the capacity provider strategy to use for the task. When capacity_provider_strategy is specified, the launch_type parameter is omitted. If no capacity_provider_strategy or launch_type is specified, the default capacity provider strategy for the cluster is used. :param group: the name of the task group associated with the task :param placement_constraints: an array of placement constraint objects to use for the task :param placement_strategy: an array of placement strategy objects to use for the task :param platform_version: the platform version on which your task is running :param network_configuration: the network configuration for the task :param tags: a dictionary of tags in the form of {'tagKey': 'tagValue'}. :param awslogs_group: the CloudWatch group where your ECS container logs are stored. Only required if you want logs to be shown in the Airflow UI after your job has finished. :param awslogs_region: the region in which your CloudWatch logs are stored. If None, this is the same as the `region` parameter. If that is also None, this is the default AWS region based on your connection settings. :param awslogs_stream_prefix: the stream prefix that is used for the CloudWatch logs. This is usually based on some custom name combined with the name of the container. Only required if you want logs to be shown in the Airflow UI after your job has finished. :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait in between each Cloudwatch logs fetches. :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle transient errors. :param reattach: If set to True, will check if the task previously launched by the task_instance is already running. If so, the operator will attach to it instead of starting a new task. This is to avoid relaunching a new task when the connection drops between Airflow and ECS while the task is running (when the Airflow worker is restarted for example). :param number_logs_exception: Number of lines from the last Cloudwatch logs to return in the AirflowException if an ECS task is stopped (to receive Airflow alerts with the logs of what failed in the code running in ECS). :param wait_for_completion: If True, waits for creation of the cluster to complete. (default: True) :param waiter_delay: The amount of time in seconds to wait between attempts, if not set then the default waiter value will be used. :param waiter_max_attempts: The maximum number of attempts to be made, if not set then the default waiter value will be used. """
[docs] ui_color = "#f0ede4"
[docs] template_fields: Sequence[str] = ( "task_definition", "cluster", "overrides", "launch_type", "capacity_provider_strategy", "group", "placement_constraints", "placement_strategy", "platform_version", "network_configuration", "tags", "awslogs_group", "awslogs_region", "awslogs_stream_prefix", "awslogs_fetch_interval", "propagate_tags", "reattach", "number_logs_exception", "wait_for_completion",
)
[docs] template_fields_renderers = { "overrides": "json", "network_configuration": "json", "tags": "json",
}
[docs] REATTACH_XCOM_KEY = "ecs_task_arn"
[docs] REATTACH_XCOM_TASK_ID_TEMPLATE = "{task_id}_task_arn"
def __init__( self, *, task_definition: str, cluster: str, overrides: dict, launch_type: str = "EC2", capacity_provider_strategy: list | None = None, group: str | None = None, placement_constraints: list | None = None, placement_strategy: list | None = None, platform_version: str | None = None, network_configuration: dict | None = None, tags: dict | None = None, awslogs_group: str | None = None, awslogs_region: str | None = None, awslogs_stream_prefix: str | None = None, awslogs_fetch_interval: timedelta = timedelta(seconds=30), propagate_tags: str | None = None, quota_retry: dict | None = None, reattach: bool = False, number_logs_exception: int = 10, wait_for_completion: bool = True, waiter_delay: int | None = None, waiter_max_attempts: int | None = None, **kwargs, ): super().__init__(**kwargs) self.task_definition = task_definition self.cluster = cluster self.overrides = overrides self.launch_type = launch_type self.capacity_provider_strategy = capacity_provider_strategy self.group = group self.placement_constraints = placement_constraints self.placement_strategy = placement_strategy self.platform_version = platform_version self.network_configuration = network_configuration self.tags = tags self.awslogs_group = awslogs_group self.awslogs_stream_prefix = awslogs_stream_prefix self.awslogs_region = awslogs_region self.awslogs_fetch_interval = awslogs_fetch_interval self.propagate_tags = propagate_tags self.reattach = reattach self.number_logs_exception = number_logs_exception if self.awslogs_region is None: self.awslogs_region = self.region self.arn: str | None = None self.retry_args = quota_retry self.task_log_fetcher: EcsTaskLogFetcher | None = None self.wait_for_completion = wait_for_completion self.waiter_delay = waiter_delay self.waiter_max_attempts = waiter_max_attempts @provide_session
[docs] def execute(self, context, session=None): self.log.info( "Running ECS Task - Task definition: %s - on cluster %s", self.task_definition, self.cluster ) self.log.info("EcsOperator overrides: %s", self.overrides) if self.reattach: self._try_reattach_task(context) self._start_wait_check_task(context) self.log.info("ECS Task has been successfully executed") if self.reattach: # Clear the XCom value storing the ECS task ARN if the task has completed # as we can't reattach it anymore self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id)) if self.do_xcom_push and self.task_log_fetcher: return self.task_log_fetcher.get_last_log_message() return None
@AwsBaseHook.retry(should_retry_eni) def _start_wait_check_task(self, context): if not self.arn: self._start_task(context) if self._aws_logs_enabled(): self.log.info("Starting ECS Task Log Fetcher") self.task_log_fetcher = self._get_task_log_fetcher() self.task_log_fetcher.start() try: if self.wait_for_completion: self._wait_for_task_ended() finally: self.task_log_fetcher.stop() self.task_log_fetcher.join() else: if self.wait_for_completion: self._wait_for_task_ended() self._check_success_task() def _xcom_del(self, session, task_id): session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete() def _start_task(self, context): run_opts = { "cluster": self.cluster, "taskDefinition": self.task_definition, "overrides": self.overrides, "startedBy": self.owner, } if self.capacity_provider_strategy: run_opts["capacityProviderStrategy"] = self.capacity_provider_strategy elif self.launch_type: run_opts["launchType"] = self.launch_type if self.platform_version is not None: run_opts["platformVersion"] = self.platform_version if self.group is not None: run_opts["group"] = self.group if self.placement_constraints is not None: run_opts["placementConstraints"] = self.placement_constraints if self.placement_strategy is not None: run_opts["placementStrategy"] = self.placement_strategy if self.network_configuration is not None: run_opts["networkConfiguration"] = self.network_configuration if self.tags is not None: run_opts["tags"] = [{"key": k, "value": v} for (k, v) in self.tags.items()] if self.propagate_tags is not None: run_opts["propagateTags"] = self.propagate_tags response = self.client.run_task(**run_opts) failures = response["failures"] if len(failures) > 0: raise EcsOperatorError(failures, response) self.log.info("ECS Task started: %s", response) self.arn = response["tasks"][0]["taskArn"] self.ecs_task_id = self.arn.split("/")[-1] self.log.info("ECS task ID is: %s", self.ecs_task_id) if self.reattach: # Save the task ARN in XCom to be able to reattach it if needed self.xcom_push(context, key=self.REATTACH_XCOM_KEY, value=self.arn) def _try_reattach_task(self, context): task_def_resp = self.client.describe_task_definition(taskDefinition=self.task_definition) ecs_task_family = task_def_resp["taskDefinition"]["family"] list_tasks_resp = self.client.list_tasks( cluster=self.cluster, desiredStatus="RUNNING", family=ecs_task_family ) running_tasks = list_tasks_resp["taskArns"] # Check if the ECS task previously launched is already running previous_task_arn = self.xcom_pull( context, task_ids=self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id), key=self.REATTACH_XCOM_KEY, ) if previous_task_arn in running_tasks: self.arn = previous_task_arn self.ecs_task_id = self.arn.split("/")[-1] self.log.info("Reattaching previously launched task: %s", self.arn) else: self.log.info("No active previously launched task found to reattach") def _wait_for_task_ended(self) -> None: if not self.client or not self.arn: return waiter = self.client.get_waiter("tasks_stopped") waiter.config.max_attempts = sys.maxsize # timeout is managed by airflow waiter.wait( cluster=self.cluster, tasks=[self.arn], WaiterConfig=prune_dict( { "Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts, } ), ) return def _aws_logs_enabled(self): return self.awslogs_group and self.awslogs_stream_prefix def _get_task_log_fetcher(self) -> EcsTaskLogFetcher: if not self.awslogs_group: raise ValueError("must specify awslogs_group to fetch task logs") log_stream_name = f"{self.awslogs_stream_prefix}/{self.ecs_task_id}" return EcsTaskLogFetcher( aws_conn_id=self.aws_conn_id, region_name=self.awslogs_region, log_group=self.awslogs_group, log_stream_name=log_stream_name, fetch_interval=self.awslogs_fetch_interval, logger=self.log, ) def _check_success_task(self) -> None: if not self.client or not self.arn: return response = self.client.describe_tasks(cluster=self.cluster, tasks=[self.arn]) self.log.info("ECS Task stopped, check status: %s", response) if len(response.get("failures", [])) > 0: raise AirflowException(response) for task in response["tasks"]: if task.get("stopCode", "") == "TaskFailedToStart": # Reset task arn here otherwise the retry run will not start # a new task but keep polling the old dead one # I'm not resetting it for other exceptions here because # EcsTaskFailToStart is the only exception that's being retried at the moment self.arn = None raise EcsTaskFailToStart(f"The task failed to start due to: {task.get('stoppedReason', '')}") # This is a `stoppedReason` that indicates a task has not # successfully finished, but there is no other indication of failure # in the response. # https://docs.aws.amazon.com/AmazonECS/latest/developerguide/stopped-task-errors.html if re.match(r"Host EC2 \(instance .+?\) (stopped|terminated)\.", task.get("stoppedReason", "")): raise AirflowException( f"The task was stopped because the host instance terminated:" f" {task.get('stoppedReason', '')}" ) containers = task["containers"] for container in containers: if container.get("lastStatus") == "STOPPED" and container.get("exitCode", 1) != 0: if self.task_log_fetcher: last_logs = "\n".join( self.task_log_fetcher.get_last_log_messages(self.number_logs_exception) ) raise AirflowException( f"This task is not in success state - last {self.number_logs_exception} " f"logs from Cloudwatch:\n{last_logs}" ) else: raise AirflowException(f"This task is not in success state {task}") elif container.get("lastStatus") == "PENDING": raise AirflowException(f"This task is still pending {task}") elif "error" in container.get("reason", "").lower(): raise AirflowException( f"This containers encounter an error during launching: " f"{container.get('reason', '').lower()}" )
[docs] def on_kill(self) -> None: if not self.client or not self.arn: return if self.task_log_fetcher: self.task_log_fetcher.stop() response = self.client.stop_task( cluster=self.cluster, task=self.arn, reason="Task killed by the user" ) self.log.info(response)

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